The manufacturing industry in Australia is particularly volatile, according to "Building Resilience in Australian Manufacturing", a report released by the non-profit industry body, the Advanced Manufacturing Growth Centre (AMGC). When our economy is booming, the average output of the industry grows by 20 per cent but shrinks by the same proportion during downturns.Such volatility can be stressful for firms looking to keep a steady ship and not go under when times get tough. So with that in mind, what can you do to make your manufacturing business more resilient?Volatility and Australian manufacturingAs stated above, the volatility in the manufacturing industry is quite aggressive. The report explains that it fluctuates with an amplitude greater than many other countries round the world - the figure for the UK is 14 per cent and is 10 per cent in the US. It's argued that this is due in part to two factors:Terms of trade volatility - Australia is a relatively small economy, whose currency is heavily traded and whose exports are influenced strongly by commodity price fluctuations.Geographic isolation - being far away from other markets means changes in shipping costs are magnified.Such dramatic changes in output can have devastating effects on manufacturing businesses. Many are vulnerable to changes in customer numbers that at first glance would seem fairly insignificant. But for 30 per cent of firms, losing one customer would result in moderate to significant negative effects on their business, and 10 per cent would be forced to shut down entirely. Needless to say, operating on such a knife edge is about as far from resilient as a business could be.Manufacturing output in Australia is subject to dramatic volatility.How do you become a more resilient manufacturer?Becoming more resilient is key for businesses if they wish to stay afloat during economic downturns. But what exactly is meant by the word resilient? The report defines a firm as resilient if their earnings growth is higher than the average of their industry in a downturn. In other words, resilient firms are the ones that are able to continue trading and prosper in all economic conditions.Manufacturers that exemplify this characteristic have three traits in common:1. SuperiorityFirms with superior products are resilient because the value they create isn't affected by the economic conditions. Often this can come down to a product or service having few or no substitutes, which means demand is unaffected by downturns. Having a superior product gives manufacturers a strong competitive advantage.Key to developing superior products is investing in research and development (R & D). The report states that 60 per cent of resilient firms invested heavily in R & D in the boom times before downturns, so when the tides turned, they were able to innovate and keep ahead of the competition.Another is to compete on value - superior products are often more expensive. If you can sell a product that provides better value, you're less likely to be affected by things like exchange rate fluctuations.2. DiversityFirms with diversity in their product mix and geographic export markets are resilient because they've spread their risk. While economy-wide downturns are always possible, having your business spread across multiple sectors means a greater chance one or more of the sectors you serve will be financially healthy.Diversity doesn't necessarily require a number of different final products. Manufacturers should, alongside selling their own assembled products, take opportunities to be part of supply chains for other firms if they have the capacity. Should your product's industry begin to wane, you can continue to remain buoyant by selling intermediary pieces to other firms. Often this can be to firms in other countries - if you aren't exporting...

Machine learning techniques have the capability to revolutionise manufacturing in the years to come. As the techniques become more advanced, their capacities will improve and their price of implementation will drop.Any effective manufacturing management solution in the 21st century needs to take advantage of the latest technology. So, how is manufacturing being changed by machine learning and other AI technologies?The state of the market todayMachine learning is still in its infancy, having burst onto the scene in 2012 and grown steadily since. Trendforce predicts the market for 'smart manufacturing solutions' will grow to nearly AUD $420 billion by 2020.How is machine learning changing manufacturing?Machine learning, however difficult to develop, is fairly easy to explain. Instead of programming computers in a linear fashion with a set of rules that guide its operation, machine learning algorithms learn from data that they're fed, without being told exactly what to do.A commonly application of machine learning, for example, is in computer vision or perception. As Michael Mendelson of the NVIDIA Deep Learning Institute told Redshift, "without flexible algorithms, computers can only do what we tell them. Many tasks, especially those involving perception, can't be translated into rule-based instructions. In a manufacturing context, some of the more immediately interesting applications will involve perception." Elements such as quality control, where a product needs to be checked for defects, may well become the common providence of machine learning algorithms in the future.Although the future is where we'll likely see machine learning applied more often, some companies are already employing it extensively. Siemens is a conglomerate that's been using machine learning techniques to monitor their factories for several years now. GE is another company that heavily utilises machine learning. Their system "Predix" takes the data generated from its factories and uses its deep learning capacities to spot potential issues and provide solutions.What's stopping more companies adopting machine learning techniques?A study by Infosys asked manufacturers what the hurdles were in their drive towards digital transformation. They cited a lack of:Data-led insights on demand (67 per cent),Collaboration among teams (51 per cent),Time (40 per cent).When asked specifically what stood in the way of adopting more AI-supported elements as part of their digital transformation strategies, they said they lacked:In-house knowledge and skills around the technology (58 per cent),Clarity around the AI value proposition (57 per cent),Financial resources (54 per cent).While it's clear machine learning has a lot of potential in the manufacturing space, there are still many hurdles standing in the way of companies adopting it. For more information on how Advanced Business Manager's software solutions can take your manufacturing operation to the next level, contact us today.